Biology subjects

Sim, H.

Publications and source records attributed to Sim, H..

6 recordsLinked to original sources

bioRxiv2026

AI-driven framework modeling perturbation in brain organoids reveals candidate genes for autism

Autism gene discovery is constrained by the rarity and heterogeneity of damaging variants, requiring large cohorts to identify susceptibility genes. Neural organoids and single-cell foundation models enable perturbation modeling in neurodevelopmental contexts. Here, we show that perturbation-informed foundation modeling of neural organoids can provide functional context for prioritizing candidate genes with genomic and clinical support. We constructed a 3.6-million-cell organoid atlas and trained models to predict genome-wide perturbation responses. Benchmarking 17 models identified a telencephalic neuron-specific model best preserving autism-relevant perturbation structure. Genome-wide profiling revealed two clusters associated with mid-fetal synaptic neuronal processes and early radial glia ubiquitin signaling. These clusters were supported by damaging-variant enrichment and clinical phenotypes across 89,916 family-based samples. Logistic-regression prioritization identified 343 candidates, including 167 in the key clusters, with convergence across TADA signals and recurrent evidence for NBEA and KLHDC10. This framework integrates predicted perturbation effects with genomic evidence to support autism candidate prioritization.

bioinformatics↗

bioRxiv2025

Ensemble quantitation of absolute metabolite concentrations in T cells reveals conserved features of immunometabolism

T cell diversity and differentiation define individual adaptive immunity. Metabolism fuels adaptive immunity by driving proliferation, differentiation, and activation; however, how individual and lineage differences shape T cell metabolism remains unknown. Here we develop an ensemble method for absolute metabolome quantitation and quantify 84 metabolites in human primary T cells. Liquid chromatography-mass spectrometry of metabolites co-extracted from T cells and 13C-labeled reference cells reveals absolute concentrations en masse. Across subtypes and individuals, T cell metabolomes resemble one another. T cells possess thermodynamically forward-driven glycolysis, high adenylate energy charge, large amino acid pools, and favorable redox ratios for anabolism and antioxidant defense. Across metabolism, metabolite concentrations exceed their associated Michaelis constants and inhibitor constants two thirds and half of the time, respectively. The conserved features of T cell metabolomes underlie a design principle: metabolite levels prime T cells for increased energy demand, oxidative stress, and rapid regulation that accompany immune response.

biochemistry↗

bioRxiv2024

Systemic CD8+ T cell effector signature predicts prognosis of lung cancer immunotherapy

BackgroundWhile immune checkpoint inhibitors (ICIs) are adopted as standard therapy in non-small cell lung cancer (NSCLC) patients, factors that influence variable prognosis still remain elusive. Therefore, a deeper understanding is needed of how germline variants regulate the transcriptomes of circulating immune cells in metastasis, and ultimately influence immunotherapy outcomes. MethodsWe collected peripheral blood mononuclear cells (PBMCs) from 73 ICI-treated NSCLC patients, conducted single-cell RNA sequencing, and called germline variants via SNP microarray. Determination of expression quantitative trait loci (eQTL) allows elucidating genetic interactions between germline variants and gene expression. Utilizing aggregation-based eQTL mapping and network analysis across eight blood cell types, we sought cell-type-specific and ICI-prognosis-dependent gene regulatory signatures. ResultsOur sc-eQTL analysis identified 3,616 blood- and 702 lung-cancer-specific eGenes across eight major clusters and treatment conditions, highlighting involvement of immune-related pathways. Network analysis revealed TBX21-EOMES regulons activity in CD8+ T cells and the enrichment of eQTLs in higher-centrality genes as predictive factors of ICI response. ConclusionsOur findings suggest that in the circulating immune cells of NSCLC patients, transcriptomic regulation differs in a cell type- and treatment-specific manner. They further highlight the role of eQTL loci as broad controllers of ICI-prognosis-predicting gene networks. The predictive networks and identification of eQTL contributions can lead to deeper understanding and personalized ICI therapy response prediction based on germline variants.

genomics↗

bioRxiv2024

Increased inflammatory signature in myeloid cells of non-small cell lung cancer patients with high clonal hematopoiesis burden

Clonal hematopoiesis of indeterminate potential (CHIP) allows estimation of clonal dynamics and documentation of somatic mutations in the hematopoietic system. Recent studies utilizing large cohorts of the general population and patients have revealed significant associations of CHIP burden with age and disease status, including in cancer and chronic diseases. An increasing number of cancer patients are treated with immune checkpoint inhibitors (ICI), but the association of ICI response in non-small cell lung cancer (NSCLC) patients with CHIP burden remains to be determined. We collected blood samples from 100 metastatic NSCLC patients before and after ICI for high-depth sequencing of the CHIP panel and 63 samples for blood single-cell RNA sequencing(scRNA-seq). Whole exome sequencing (WES) was performed in an independent replication cohort of 180 patients. The impact of CHIP status on the immunotherapy response was not significant. However, metastatic lung cancer patients showed higher CHIP prevalence (44/100 for patients vs 5/42 for controls; P = 0.01). In addition, lung squamous cell carcinoma patients showed increased burden of larger clones compared to lung adenocarcinoma patients (8/43 for LUSC vs 2/50 for LUAD; P = 0.04). Furthermore, single cell RNA-seq analysis of the matched patients showed significant enrichment of inflammatory pathways mediated by NF-B in myeloid clusters of the severe CHIP group. Our findings suggest minimal involvement of CHIP mutation and clonal dynamics during immunotherapy but a possible role of CHIP as an indicator of immunologic response in NSCLC patients.

genomics↗

bioRxiv2021

Disease-specific eQTL screening reveals an anti-fibrotic effect of AGXT2 in nonalcoholic fatty liver disease

Background & AimsNonalcoholic fatty liver disease (NAFLD) poses an impending clinical burden. Genome-wide association studies have revealed a limited contribution of genomic variants to the disease, requiring alternative but robust approaches to identify disease-associated variants and genes. We carried out a disease-specific expression quantitative trait loci (eQTL) screen to identify novel genetic factors that specifically act on NAFLD progression on the basis of genotype. MethodsWe recruited 125 Korean biopsy-proven NAFLD patients and healthy individuals and performed eQTL analyses using 21,272 transcripts and 3,234,941 genotyped and imputed SNPs. We then selected eQTLs that were detected only in the NAFLD group, but not in the control group (i.e., NAFLD-eQTLs). An additional cohort of 162 Korean NAFLD individuals was used for replication. The function of the selected eQTL toward NAFLD development was validated using HepG2, primary hepatocytes and NAFLD mouse models. ResultsThe NAFLD-specific eQTL screening yielded 242 loci. Among them, AGXT2, encoding alanine-glyoxylate aminotransferase 2, displayed decreased expression in NAFLD patients homozygous for the non-reference allele of rs2291702, compared to no-NAFLD subjects with the same genotype (P = 4.79 x 10-6). This change was replicated in an additional 162 individuals, yielding a combined P-value of 8.05 x 10-8 from a total of 245 NAFLD patients and 48 controls. Knockdown of AGXT2 induced palmitate-overloaded hepatocyte death by increasing ER stress, and exacerbated NAFLD diet-induced liver fibrosis in mice. However, overexpression of AGXT2 reversely attenuated liver fibrosis and steatosis as well. ConclusionsWe implicate a new molecular role of AGXT2 in NAFLD. Our overall approach will serve as an efficient tool for uncovering novel genetic factors that contribute to liver steatosis and fibrosis in patients with NAFLD. Lay summaryElucidating causal genes for NAFLD has been challenging due to limited tissue availability and the polygenic nature of the disease. Using liver and blood samples from 125 biopsy-proven NAFLD and no-NAFLD Korean individuals and an additional 162 individuals for replication, we devised a new analytic method to identify causal genes. Among the candidates, we found that AGXT2-rs2291702 protects against liver fibrosis in a genotype-dependent manner with the potential for therapeutic interventions. Our approach enables the discovery of NAFLD causal genes that act on the basis of genotype.

genetics↗

bioRxiv2020

Activity-based urinary biomarkers of response and resistance to checkpoint blockade immunotherapy

Immune checkpoint blockade (ICB) therapy has transformed cancer treatment, yet most patients do not derive clinical benefit and responders can acquire resistance to therapy. Noninvasive biomarkers are needed to indicate early on-treatment response and resistance mechanisms. Here we developed ImmuNe Sensors for monItorinG cHeckpoint blockade Therapy (INSIGHT), which comprises a library of mass-barcoded peptide substrates conjugated to PD1 antibodies, as therapeutic sensors. Following systemic administration, INSIGHT carries out the dual role of reinvigorating T cell function and profiling T cell and tumor proteases by the release of cleaved peptides into urine for noninvasive detection by mass spectrometry. We show that an PD1 therapeutic sensor for Granzyme B discriminates early treatment responses before tumor volumes significantly diverge from isotype controls in murine models of colorectal cancer. To differentiate mechanisms of resistance by multivariate analysis, we design a mass-barcoded, 14-plex INSIGHT library to profile proteases differentially expressed by tumors harboring B2m or Jak1 loss-of-function mutations. We find that binary classifiers trained on urine samples indicate response to PD-1 therapy as early as the start of the second dose, and discriminate B2m from Jak1 resistance with high sensitivity and specificity (AUROCs > 0.9). Our data supports the use of activity-based biomarkers for early on-treatment response assessment and classification of refractory tumors based on resistance mechanisms. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=109 SRC="FIGDIR/small/420265v2_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@12ce799org.highwire.dtl.DTLVardef@118fcc5org.highwire.dtl.DTLVardef@17b227eorg.highwire.dtl.DTLVardef@115a7fc_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗